Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Facial recognition systems may automatically identify faces in images or videos. They can be used in, for example, automatic face login, face verification, face identification, face based visual search and character clustering, and video surveillance applications. These systems may be used on various devices, such as smart cameras, smart phones, smart TVs, PCs, laptops, tablets, and web servers.
However, accurate and robust face recognition is challenging in practical use due to variations in image data received by these systems. For example, image data may vary in illumination, face pose, expression, accessory, occlusion, and/or other factors. Existing techniques and systems may perform comparison over extraneous facial image data, resulting in inefficient computation and delays in performing recognition. Additionally, existing recognition techniques may exhibit strong dependence on their training data and develop identification thresholds which are inefficient when used with other data. When performing recognition on test data other than the data the techniques were trained on, existing techniques may demonstrate less-than-desired recognition accuracy. Further, recognition of faces which are displayed in video may prove particularly challenging as the face may change from image frame to image frame, or from moment to moment in the video.